Precision Mold Production and Manufacturing System Based on MES System

Abstract

The present invention relates to the technical field of data processing, and specifically relates to a precision mold production and manufacturing system based on an MES system, including: obtaining an accuracy adjustment coefficient for each parameter data according to the accuracy of each historical mold, the parameter data during the processing, the accuracy of each reference historical mold, and the parameter data during the processing of each reference historical mold; obtaining a processing error coefficient for each parameter data according to each parameter data during the processing of the historical mold and the accuracy adjustment coefficient for each parameter data; obtaining a corrected processing error coefficient for each parameter data according to each parameter data, the accuracy, and the processing error coefficient for each parameter data during each processing of each historical mold; constructing an updated parameter range for each parameter data according to the corrected processing error coefficient for each parameter during each processing of each historical mold, and performing precision mold production and manufacturing. The present invention improves the accuracy of abnormal analysis of the result parameters of mold processing.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and particularly to a precision mold production and manufacturing system based on the MES system. Background Art

[0002] With the rapid development of the manufacturing industry, the demand for precision molds is increasing day by day, especially in the fields of automobiles, electronics, aerospace, etc. In modern manufacturing, the MES system has become a key bridge connecting the enterprise resource planning (ERP) system and workshop automation equipment. It can provide decision-making support for production managers by collecting and analyzing various data in the production process in real time, thereby optimizing the production process and improving production efficiency and quality. Although the MES system has generally improved the production management level, in the production process of precision molds, there are multiple complex processing steps, and each step requires precise control of various processing parameters to ensure the quality and accuracy of the molds. In the actual production process, due to various reasons, some molds may not meet the standards, which will affect the production efficiency and increase the production cost. Existing MES systems often can only provide parameter anomaly analysis for a single processing step, and cannot comprehensively consider the mutual influence between consecutive processing steps, reducing the accuracy of parameter anomaly analysis of the mold processing results. Summary of the Invention

[0003] The present invention provides a precision mold production and manufacturing system based on the MES system to solve the problem that existing MES systems often can only provide parameter anomaly analysis for a single processing step, and cannot comprehensively consider the mutual influence between consecutive processing steps, reducing the accuracy of parameter anomaly analysis of the mold processing results.

[0004] The precision mold production and manufacturing system based on the MES system of the present invention adopts the following technical solutions:

[0005] An embodiment of the present invention provides a precision mold production and manufacturing system based on the MES system, and the system includes the following modules:

[0006] Data acquisition module: used to obtain multi-dimensional data of several historical mold processing results and each parameter data in each processing process;

[0007] Mold precision analysis module: used to obtain the standard range of each dimension data of the historical mold processing results; according to the standard range of each dimension data of the historical mold processing results and each dimension data, obtain the precision of each dimension data; according to the precision of all dimension data, obtain the precision of each historical mold;

[0008] Adjustment Coefficient Module for Precision of Die Processing Parameters: Used to obtain the similarity between any two historical dies based on the parameter data during the processing of each historical die; obtain the reference historical die for each historical die based on the similarity between any two historical dies; obtain the precision adjustment coefficient for each parameter data based on the precision of each historical die, the parameter data during the processing, the precision of each reference historical die, and the parameter data during the processing of each reference historical die.

[0009] Die Processing Error Coefficient Module: Used to obtain the processing error coefficient for each parameter data based on each parameter data during the processing of the historical die and the precision adjustment coefficient for each parameter data; obtain the corrected processing error coefficient for each parameter data based on each parameter data during the processing of each historical die, the precision, and the processing error coefficient for each parameter data.

[0010] Parameter Range Analysis Module during Die Processing: Used to construct the updated parameter range for each parameter data based on the corrected processing error coefficient of each parameter during the processing of each historical die for precision die production and manufacturing.

[0011] Preferably, obtaining the precision of each dimension data based on the standard range and each dimension data of each dimension data of the historical die processing result includes:

[0012]

[0013] In the formula, y r,1 represents the lower limit of the standard range of the r-th dimension data of the historical die processing result; y r,2 represents the upper limit of the standard range of the r-th dimension data of the historical die processing result; Y i,r represents the r-th dimension data of the processing result of the i-th historical die; a is a preset judgment threshold; D i,r represents the precision of the r-th dimension data of the processing result of the i-th historical die; || is the absolute value function.

[0014] Preferably, obtaining the precision of each historical die based on the precision of all dimension data includes:

[0015] Denote the minimum value among the precisions of all dimension data of the processing result of the i-th historical die as the precision of the i-th historical die.

[0016] Preferably, obtaining the similarity between any two historical dies based on the parameter data during the processing of each historical die includes:

[0017] Among any two historical dies, denote the average value of the absolute values of the differences of all the same parameter data in all the same processing procedures as the similarity between any two historical dies.

[0018] Preferably, obtaining the reference historical mold of the historical mold according to the similarity of any two historical molds includes:

[0019] Denote the top K historical molds with the greatest similarity to the i-th historical mold as the reference historical molds of the i-th historical mold; where K is a preset first threshold value.

[0020] Preferably, obtaining the accuracy adjustment coefficient of each parameter data according to the accuracy of each historical mold, the parameter data during the processing, the accuracy of each reference historical mold, and the parameter data during the processing of each reference historical mold includes:

[0021]

[0022] In the formula, R p,q represents the accuracy adjustment coefficient of the q-th parameter data in the p-th processing of the historical mold; C i represents the accuracy of the i-th historical mold; C i,j represents the accuracy of the j-th reference historical mold of the i-th historical mold; X i,p,q represents the q-th parameter data in the p-th processing of the i-th historical mold; X i,j,p,q represents the q-th parameter data in the p-th processing of the j-th reference historical mold of the i-th historical mold; Q i,p represents the number of all reference historical molds corresponding to the i-th historical mold; Q represents the number of all historical molds; norm() is a normalization function; || is an absolute value function.

[0023] Preferably, obtaining the processing error coefficient of each parameter data according to each parameter data during the processing of the historical mold and the accuracy adjustment coefficient of each parameter data includes:

[0024]

[0025] In the formula, L i,p,q represents the processing error coefficient of the q-th parameter data in the p-th processing of the i-th historical mold; X i,p,q represents the q-th parameter data in the p-th processing of the i-th historical mold; R p,q represents the accuracy adjustment coefficient of the q-th parameter data in the p-th processing of the historical mold; b is a preset value; EX p,q represents the mean value of the q-th parameter data in the p-th processing of all historical molds; σ(X p,q ) represents the standard deviation of the q-th parameter data in the p-th processing of all historical molds.

[0026] Preferably, obtaining the corrected machining error coefficient of each parameter data according to each parameter data, precision, and machining error coefficient of each parameter data in each machining process of each historical mold includes:

[0027]

[0028] In the formula, L' i,p,q represents the corrected machining error coefficient of the q-th parameter data in the p-th machining process of the i-th historical mold; L i,p,q represents the machining error coefficient of the q-th parameter data in the p-th machining process of the i-th historical mold; C i represents the precision of the i-th historical mold; n i,u represents the number of all parameter data in the u-th machining process of the i-th historical mold; p i represents the number of all machining processes in the i-th historical mold; L i,u,v represents the machining error coefficient of the v-th parameter data in the u-th machining process of the i-th historical mold.

[0029] Preferably, constructing the updated parameter range of each parameter data according to the corrected machining error coefficient of each parameter in each machining process of each historical mold includes:

[0030] When the absolute value of the corrected machining error coefficient of the q-th parameter data in the p-th machining process of the i-th historical mold is less than the preset threshold T, it is determined that the q-th parameter data in the p-th machining process of the i-th historical mold is within the normal parameter range;

[0031] Construct the updated parameter range of the q-th parameter data in each machining process of the historical mold according to the magnitudes of all parameter data of the q-th parameter data within the normal parameter range in each machining process of all historical molds.

[0032] Preferably, constructing the updated parameter range of the q-th parameter data in each machining process of the historical mold according to the magnitudes of all parameter data of the q-th parameter data within the normal parameter range in each machining process of all historical molds includes:

[0033] Construct the updated parameter range of the q-th parameter data in each machining process of the historical mold with the maximum and minimum values of all parameter data of the q-th parameter data within the normal parameter range in each machining process of all historical molds.

[0034] The beneficial effects of the technical solution of the present invention are as follows: Through the data acquisition and monitoring module of the MES system, during the production process of multiple identical molds, multiple key parameter information in each processing process is respectively obtained; through the quality management module, the precision information of each mold is quantified, and combined with the precision information and historical processing parameters, the optimal range of each parameter is analyzed through the calculation module, and then the key parameters in the production process of subsequent molds are further adjusted through the production scheduling module to ensure the accuracy of the obtained mold precision. The precision adjustment coefficient module for mold processing parameters: used to calculate the similarity between any two historical molds according to the parameter data in the processing process of each historical mold; according to the similarity between any two historical molds, obtain the reference historical mold of the historical mold; according to the precision of each historical mold, the parameter data in the processing process, the precision of each reference historical mold, and the parameter data in the processing process of each reference historical mold, obtain the precision adjustment coefficient of each parameter data; The mold processing error coefficient module: used to obtain the processing error coefficient of each parameter data according to each parameter data in the processing process of the historical mold and the precision adjustment coefficient of each parameter data; according to each parameter data, precision, and processing error coefficient of each parameter data in each processing process of each historical mold, obtain the corrected processing error coefficient of each parameter data; adjusting each parameter in the processing process of the mold improves the accuracy of abnormal analysis of the processing result parameters of the mold, and helps to improve the processing precision of subsequent molds. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0036] Figure 1 It is a module flowchart of the precision mold production and manufacturing system based on the MES system of the present invention;

[0037] Figure 2 It is a production manufacturing flowchart of the precision mold based on the MES system of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0038] To further elaborate on the technical means and effects adopted by the present invention to achieve the intended invention purpose, the following specifically describes, in conjunction with the accompanying drawings and preferred embodiments, the specific implementation manner, structure, features, and effects of the precision mold production and manufacturing system based on the MES system proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0039] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which the present invention belongs.

[0040] The following specifically describes, in conjunction with the accompanying drawings, the specific solution of the precision mold production and manufacturing system based on the MES system provided by the present invention.

[0041] Please refer to Figure 1 , which shows the module flowchart of the precision mold production and manufacturing system based on the MES system provided by an embodiment of the present invention. The system includes the following modules:

[0042] Module 101: Data acquisition module.

[0043] The data acquisition module is used to obtain multi-dimensional data of several historical mold processing results and each parameter data in each processing process.

[0044] It should be noted that the production process of precision molds includes various different processing processes, and due to the influence of different parameter changes in previous processing processes, the obtained molds may not necessarily meet the required precision and quality standards. Therefore, by analyzing the processing parameter data in each processing process and the performance standards of the obtained molds, the parameter anomalies in each different processing process are analyzed, and then timely adjustment is made through the MES system to further improve the precision of the molds.

[0045] Collect the processing process data and processing result data of historical molds through the MES system; the MES system refers to the Manufacturing Execution System, which is an information system used to monitor and manage the manufacturing process. It is usually located between the enterprise resource planning system and the field control system and serves as a bridge connecting the production plan and on-site operations.

[0046] The influencing parameters of each step in the historical mold processing process are as follows:

[0047] CNC machining: cutting speed, feed speed, cutting depth, cutting width;

[0048] Electrical Discharge Machining: Pulse width, Pulse interval, Discharge current magnitude, Electrode gap;

[0049] Wire Electrical Discharge Machining: Wire feed speed, Power supply voltage, Discharge pulse width time, Discharge pulse interval time, Discharge current peak value;

[0050] Deep Hole Drilling: Drill speed, Feed rate, Coolant pressure, Flow rate, Drill bit geometric parameters;

[0051] Obtain each parameter data during each machining process of several historical molds;

[0052] It should be noted that after obtaining the machined mold, measure multiple key dimensions of the mold respectively, check whether they are within the designed tolerance range, and measure the surface roughness of the mold with a roughness meter to check whether its surface finish meets the design requirements. Measure the surface roughness of the mold with a roughness meter to obtain the roughness of multiple key dimensions and multiple key surfaces in the machining result information.

[0053] Obtain multi-dimensional data of the machining results of several historical molds. The data after the machining of historical molds are such as geometric dimensions, surface roughness, material hardness, process parameters, dimension measurement data, etc.

[0054] Standardize the multi-dimensional data of the machining results of several historical molds and all parameter data during each machining process, and use Z-score standardization to unify the dimension;

[0055] Among them, Z-score standardization is a well-known technology, and the specific method will not be introduced here.

[0056] It should be noted that obtain data such as multiple geometric dimensions and surface roughness in the machining result information, and conduct subsequent analysis according to multiple parameters obtained during different machining processes of the mold and the parameters of the mold.

[0057] Obtain multi-dimensional data of the machining results of several historical molds; obtain each parameter data during each machining process of several historical molds.

[0058] Module 102: Mold Precision Analysis Module.

[0059] Mold Precision Analysis Module: Used to obtain the standard range of each dimension data of the machining results of historical molds; obtain the precision of each dimension data according to the standard range of each dimension data of the machining results of historical molds and each dimension data; obtain the precision of each historical mold according to the precision of all dimension data.

[0060] It should be noted that after obtaining the processing result information corresponding to multiple historical molds, considering that there will be certain differences in the accuracy among different molds under the results of different processing parameter information, the accuracy of some samples may not reach the established indicators.

[0061] According to the regulations in the design specification, obtain the upper and lower limits of the standard for each processing result data of the historical molds;

[0062] Obtain the standard range of the r-th dimension data of the processing results of the historical molds, denoted as [y r,1 , y r,2 ;

[0063] The preset judgment threshold a is 1;

[0064] The calculation method for the accuracy of the r-th dimension data of the processing result of the i-th historical mold is as follows:

[0065]

[0066] In the formula, y r,1 represents the lower limit of the standard range of the r-th dimension data of the processing result of the historical mold; y r,2 represents the upper limit of the standard range of the r-th dimension data of the processing result of the historical mold; Y i,r represents the r-th dimension data of the processing result of the i-th historical mold; a is the preset judgment threshold; D i,r represents the accuracy of the r-th dimension data of the processing result of the i-th historical mold; || is the absolute value function.

[0067] Calculate and obtain the accuracy of each dimension data of the processing result of the i-th historical mold in the above manner;

[0068] Record the minimum value among the accuracies of all dimension data of the processing result of the i-th historical mold as the accuracy of the i-th historical mold.

[0069] It should be noted that set the accuracy of the molds whose processing result data of the historical molds exceed the specified range to 0; and assign a higher accuracy to the mold whose processing result data of the historical molds is closest to the median of the specified range.

[0070] Thus, the accuracy of each historical mold is obtained.

[0071] Module 103: Adjustment Coefficient Module for Mold Processing Parameter Accuracy.

[0072] Mold processing parameter accuracy adjustment coefficient module: used to obtain the similarity between any two historical molds based on the parameter data during the processing of each historical mold; obtain the reference historical mold of the historical mold according to the similarity between any two historical molds; obtain the accuracy adjustment coefficient of each parameter data according to the accuracy of each historical mold, the parameter data during the processing, the accuracy of each reference historical mold, and the parameter data during the processing of each reference historical mold.

[0073] It should be noted that after obtaining the processing accuracy of each mold, considering that different processing parameters are selected during different processing processes of each mold, the multi-dimensional processing parameter data obtained includes a lot of redundant data. For example, in the numerical control processing process, the cutting speed and feed speed have a greater impact on the final result. Under a fixed mold, the cutting depth and cutting width at different key dimensions are relatively fixed. When the processing process is abnormal, more consideration should be given to whether the cutting speed is abnormal. Therefore, it is necessary to consider the influence of different parameters in different processing processes on the final mold accuracy, and then more precisely control the parameter dimensions with greater subsequent influence, which can further improve the processing accuracy of the mold.

[0074] It should be noted that under multiple different mold samples, when each parameter in each processing process has a greater impact on the final accuracy, when the remaining parameters remain stable, if a dimensional parameter fluctuates within a small range, the change in its final accuracy is relatively large, and a larger accuracy adjustment coefficient should be assigned to it.

[0075] It should be noted that first, the similarity between the processing parameters of two molds should be obtained. It is necessary to ensure that the processing parameters between the two molds are relatively similar in the remaining dimensional parameters, so as to highlight the influence of the change of a single parameter on the accuracy; calculate the similarity between any two historical molds.

[0076] In any two historical molds, the mean value of the absolute values of the differences of all the same parameter data in all the same processing processes is recorded as the similarity between any two historical molds.

[0077] The specific calculation method of the similarity between the i-th historical mold and the k-th historical mold except the i-th historical mold is as follows:

[0078]

[0079] In the formula, H i,k represents the similarity between the i-th historical mold and the k-th historical mold except the i-th historical mold; X i,p,q represents the q-th parameter data in the p-th processing process of the i-th historical mold; X k,p,qDenote the q-th parameter data in the p-th processing procedure of the k-th historical die among the first i historical dies; || is the absolute value function; P is the number of processing procedures for each historical die; Q p is the number of parameter data in the p-th processing procedure for each historical die.

[0080] Preset the first threshold K to be 5, and denote the top K historical dies with the greatest similarity to the i-th historical die as the reference historical dies of the i-th historical die;

[0081] The calculation method of the precision adjustment coefficient of the q-th parameter data in the p-th processing procedure of a historical die is as follows:

[0082]

[0083] In the formula, R p,q denotes the precision adjustment coefficient of the q-th parameter data in the p-th processing procedure of a historical die; C i denotes the precision of the i-th historical die; C i,j denotes the precision of the j-th reference historical die of the i-th historical die; X i,p,q denotes the q-th parameter data in the p-th processing procedure of the i-th historical die; X i,j,p,q denotes the q-th parameter data in the p-th processing procedure of the j-th reference historical die of the i-th historical die; Q i,p denotes the number of all reference historical dies corresponding to the i-th historical die; Q denotes the number of all historical dies; norm() is the normalization function; || is the absolute value function.

[0084] Thus, the precision adjustment coefficient of each parameter data in the processing procedure of the historical die is obtained.

[0085] Module 104: Die processing error coefficient module.

[0086] The die processing error coefficient module: is used to obtain the processing error coefficient of each parameter data according to each parameter data and the precision adjustment coefficient of each parameter data in the processing procedure of the historical die; and obtain the corrected processing error coefficient of each parameter data according to each parameter data, precision, and the processing error coefficient of each parameter data in each processing procedure of each historical die.

[0087] It should be noted that considering the traditional anomaly detection method, for a single dimension, generally the difference from the mean is selected for quantification. However, for parameters with different impacts on the final precision in each dimension, different quantification methods of the processing error coefficient should be assigned to dimensions with different precision adjustment coefficients.

[0088] It should be noted that by assigning different normalization criteria to different dimensions, for the parameter dimension with a higher adjustment coefficient, when the parameter value has a small difference compared to the mean, a higher processing error coefficient should be assigned to it.

[0089] The preset value b is 3;

[0090] The calculation method of the processing error coefficient of the qth parameter data in the pth processing of the ith historical mold is as follows:

[0091]

[0092] In the formula, L i,p,q represents the processing error coefficient of the qth parameter data in the pth processing of the ith historical mold; X i,p,q represents the qth parameter data in the pth processing of the ith historical mold; R p,q represents the precision adjustment coefficient of the qth parameter data in the pth processing of the historical mold; b is the preset value; EX p,q represents the mean value of the qth parameter data of all historical molds in the pth processing; σ(X p,q ) represents the standard deviation of the qth parameter data of all historical molds in the pth processing.

[0093] It should be noted that the above takes into account that the parameter data of each dimension has different influences on the final mold precision, so their precision adjustment coefficients are used respectively; when the precision adjustment coefficient of the qth parameter in the pth processing is small, the influence of this dimension parameter on the final precision is small. At this time, when the outlier degree of this dimension data is high, its processing error coefficient is high, that is, the ratio between X i,p,q -EX p,q and 3σ is used to judge the processing error coefficient; conversely, the influence of this dimension data on the final precision is large, and the outlier degree X i,p,q -EX p,q is compared with one times of σ, so that when the change of this dimension data is small, its processing error coefficient will be high.

[0094] It should be noted that considering the machining process of the mold, each machining step will change the physical state and geometric characteristics of the workpiece, and the previous machining process will affect the parameters used in the subsequent machining process; for example, electrical discharge machining will generate a heat affected zone on the workpiece surface, and different current magnitudes will cause different degrees of changes in the microstructure and hardness of the material, which will in turn affect the tool selection and cutting parameters of the subsequent machining to meet the final machining precision; the adjustment method often depends on the machine tool operation manual or a fixed parameter range, and it is difficult to ensure the consistency and repeatability of machining.

[0095] It should be noted that considering the relationships among various processing parameters during different processing procedures, when the parameters of a certain processing procedure are relatively abnormal, not only the difference between a single parameter dimension and the mean value needs to be considered, but also whether some parameters have been abnormal before needs to be considered. When the final accuracy is low, some parameter abnormalities during the processing procedure should receive more attention.

[0096] The calculation method of the corrected processing error coefficient of the q-th parameter data in the p-th processing procedure of the i-th historical mold is as follows:

[0097]

[0098] In the formula, L' i,p,q represents the corrected processing error coefficient of the q-th parameter data in the p-th processing procedure of the i-th historical mold; L i,p,q represents the processing error coefficient of the q-th parameter data in the p-th processing procedure of the i-th historical mold; C i represents the accuracy of the i-th historical mold; n i,u represents the quantity of all parameter data in the u-th processing procedure of the i-th historical mold; p i represents the quantity of all processing procedures in the i-th historical mold; L i,u,v represents the processing error coefficient of the v-th parameter data in the u-th processing procedure of the i-th historical mold; adding 1 to the denominator in the formula is to prevent the denominator from being 0.

[0099] Thus, the corrected processing error coefficient of each parameter in each processing procedure of each historical mold is obtained.

[0100] Module 105: Parameter range analysis module during mold processing.

[0101] The parameter range analysis module during mold processing: is used to construct the updated parameter range of each parameter data according to the corrected processing error coefficient of each parameter in each processing procedure of each historical mold, so as to carry out the production and manufacturing of precision molds.

[0102] It should be noted that according to the above calculation method, the magnitudes of the corrected processing error coefficients of each parameter in multiple processing procedures of multiple historical molds are calculated respectively. When the absolute value of the corrected processing error coefficient of the q-th parameter data in the p-th processing procedure of the i-th historical mold is less than the preset threshold, it is considered that the parameter is within a normal parameter range during this mold manufacturing process; then, the maximum and minimum values of the values of each parameter after removing the abnormal parameters are calculated respectively, and thus the parameter range in each processing procedure can be obtained.

[0103] The corrected processing error coefficient of each parameter in each processing procedure of each historical mold is obtained as above;

[0104] The preset threshold value T is 1.2. When the absolute value of the correction processing error coefficient of the q-th parameter data in the p-th processing process of the i-th historical mold is less than the preset threshold value T, it is determined that the q-th parameter data in the p-th processing process of the i-th historical mold is within the normal parameter range;

[0105] According to the above method, it is calculated whether the q-th parameter data in each processing process of all historical molds is within the normal parameter range.

[0106] Using the maximum and minimum values among all the parameter data for which the q-th parameter data in each processing process of all historical molds is within the normal parameter range, the updated parameter range of the q-th parameter data in each processing process of the historical molds is constructed.

[0107] According to the updated parameter range of each parameter data in each processing process of the historical molds, it is used for precision mold production and manufacturing.

[0108] It should be noted that after obtaining the multi-dimensional processing data of multiple historical mold samples through the obtained MES system, as the number of processed parts of the same mold sample increases, after obtaining the processed mold each time, the value range of the real-time change of each parameter is obtained through the calculation module of the MES. Furthermore, in the subsequent mold processing process, the optimal value of each parameter is further determined. Through the calculation results of the MES system, in the subsequent new mold manufacturing process, the parameter range of the new mold can be optimized, thereby improving the production accuracy of the subsequent molds.

[0109] It should be noted that in this embodiment, when the denominator in the formula is 0, the denominator is set to 1, and this is used as an example for description.

[0110] The flowchart of precision mold production and manufacturing based on the MES system in this embodiment is as Figure 2 shown.

[0111] So far, this embodiment is completed.

[0112] The above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. The precision mold production and manufacturing system based on the MES system is characterized by: The system includes the following modules: Data acquisition module: used to obtain multi-dimensional data of several historical mold processing results and each parameter data in each processing process; Mold precision analysis module: used to obtain the standard range of each dimension data of the historical mold processing results; according to the standard range of each dimension data of the historical mold processing results and each dimension data, the precision of each dimension data is obtained; according to the precision of all dimension data, the precision of each historical mold is obtained; Adjustment coefficient module for mold processing parameter accuracy: used to obtain the similarity of any two historical molds based on the parameter data during the processing of each historical mold; According to the similarity of any two historical molds, a reference historical mold of the historical mold is obtained, including: The most similar previous A historical mold, recorded as Reference historical molds of historical molds; among them, A first threshold is preset; according to the accuracy of each historical mold, the parameter data during the processing, the accuracy of each reference historical mold, and the parameter data during the processing of each reference historical mold, the accuracy adjustment coefficient of each parameter data is obtained, including: In the formula, Indicates the historical mold In the processing The precision adjustment coefficient of parameter data; Indicates The accuracy of a historical mold; Indicates The first historical mold The accuracy of a reference historical mold; Indicates The first historical mold In the processing process parameter data; Indicates The first historical mold Reference to historical mold In the processing process parameter data; Indicates The number of all reference historical molds corresponding to the historical mold; Indicates the number of all historical molds; is the normalization function; is the absolute value function; Mold processing error coefficient module: used to obtain the processing error coefficient of each parameter data according to each parameter data and the accuracy adjustment coefficient of each parameter data in the historical mold processing process, including: In the formula, Indicates The first historical mold In the processing process Processing error coefficient of parameter data; is the default value; Indicates that all historical molds are in In the processing process The mean of parameter data; Indicates that all historical molds are in In the processing process The standard deviation of the parameter data; According to each parameter data, precision and processing error coefficient of each parameter data in each processing process of each historical mold, the corrected processing error coefficient of each parameter data is obtained, including: In the formula, Indicates The first historical mold In the processing process Correction processing error coefficient of parameter data; Indicates The first historical mold The number of all parameter data in a processing process; Indicates The number of all processing processes in a historical mold; Indicates The first historical mold In the processing process Processing error coefficient of parameter data; Parameter range analysis module during mold processing: used to construct the updated parameter range of each parameter data according to the corrected processing error coefficient of each parameter in each processing process of each historical mold, so as to carry out precision mold production and manufacturing.

2. According to the precision mold production and manufacturing system based on the MES system according to claim 1, it is characterized in that: The accuracy of each dimensional data obtained according to the standard range of each dimensional data of the historical mold processing results and each dimensional data includes: In the formula, Indicates the historical mold processing results. The lower limit of the standard range of the dimension data; Indicates the historical mold processing results. The upper limit of the standard range of the dimension data; Indicates The first of the historical mold processing results Dimensional data; is the preset judgment threshold; Indicates The first of the historical mold processing results The accuracy of the data in each dimension; is the absolute value function.

3. According to the precision mold production and manufacturing system based on the MES system according to claim 1, it is characterized in that: The accuracy of each historical mold obtained based on the accuracy of all dimensional data includes: The first The minimum value of all dimensional data precisions of the historical mold processing results is recorded as The accuracy of a historical mold.

4. According to the precision mold production and manufacturing system based on the MES system according to claim 1, it is characterized in that: The similarity between any two historical molds obtained according to the parameter data during the processing of each historical mold includes: In any two historical molds, the average of the absolute values ​​of the differences of all the same parameter data in the same processing process is recorded as the similarity of any two historical molds.

5. According to the MES system-based precision mold production and manufacturing system of claim 1, it is characterized in that: The updating parameter range of each parameter data is constructed according to the corrected processing error coefficient of each parameter in each processing process of each historical mold, including: When The first historical mold In the processing process The absolute value of the corrected processing error coefficient of parameter data is less than the preset threshold When The first historical mold In the processing process The parameter data are within the normal parameter range; According to the first The size of all parameter data within the normal parameter range is constructed to build the first parameter data in each processing process of the historical mold. Update parameter range for each parameter data.

6. According to the precision mold production and manufacturing system based on the MES system according to claim 5, it is characterized in that: According to the above, each processing process of all historical molds The size of all parameter data within the normal parameter range is constructed to build the first parameter data in each processing process of the historical mold. The update parameter range of each parameter data includes: Take all the historical molds in each processing process The maximum and minimum values ​​of all parameter data in the normal parameter range are constructed to construct the first parameter data in each processing process of the historical mold. Update parameter range for each parameter data.

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